Data science skills as integrators: diffusion of the algorithmic power in contemporary Chinese labor market

Data science-related skills are transforming Chinese labor market in the AI era. By conceptualizing the labor market as a dynamic skill network, we argue that data science skills act as integrators, connecting previously disconnected domain-specific skill clusters across different occupations and consolidating algorithmic control. Using a large-scale dataset of high-skill job postings from liepin.com, we leverage LLM-based data extraction, classification, and network analysis to trace the diffusion of data science skills and their integration with two occupations leading this diffusion in the labor market: biomedicine and finance. Results demonstrate a marked increase in network density and the inter-occupational ties between data science and the other two occupations from 2015 to 2023, integrated by a few key skills in data science. The effect of data science skills on inter-occupational integration exceeds that of the overall network density growth. Making progress in using Retrieval-Augmented Generation (RAG) to solve the extreme multilabel text classification (XMTC) problem in large-scale, unstructured Chinese textual data at the job level, our analyses illustrate how data science is reshaping human capital, influencing work dynamics, and driving organizational change.